Skip to main content
SpringerLink
Log in

Soot: A review of computational models at different length scales

  • Review Article
  • Published:
Experimental and Computational Multiphase Flow Aims and scope Submit manuscript

Abstract

The computational modelling of soot formation and destruction during the combustion process is one of the most challenging topics in combustion research. This paper reviews the numerical soot models constructed at different length scales, including macroscale, mesoscale, and microscale. The four key stages of soot evolution, including nucleation, surface growth and coagulation, agglomeration, and oxidation, are first described with the generally accepted mathematical formulations in each stage explained. Different computational frameworks and their pros and cons are then reviewed, including the one-equation empirical soot model (macroscale), two-equation semi-empirical soot model (macroscale), different variations of population balance model (mesoscale), discrete element model (microscale), and molecular dynamics model (microscale). It is concluded that the accuracy required and the computational cost available are the two major influencing factors to be considered when selecting the appropriate computational model. The user needs to assess the priorities in their specific application and evaluate different modelling options to find the optimal balance between the level of accuracy and computation resources required.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Artelt, C., Schmid, H. J., Peukert, W. 2003. On the relevance of accounting for the evolution of the fractal dimension in aerosol process simulations. J Aerosol Sci, 34: 511–534.

    Article  Google Scholar 

  • Aubagnac-Karkar, D., El Bakali, A., Desgroux, P. 2018a. Soot particles inception and PAH condensation modelling applied in a soot model utilizing a sectional method. Combust Flame, 189: 190–206.

    Article  Google Scholar 

  • Aubagnac-Karkar, D., Michel, J. B., Colin, O., Darabiha, N. 2018b. Combustion and soot modelling of a high-pressure and high-temperature dodecane spray. Int J Engine Res, 19: 434–448.

    Article  Google Scholar 

  • Bai, X. S., Balthasar, M., Mauss, F., Fuchs, L. 1998. Detailed soot modeling in turbulent jet diffusion flames. Symp Combust, 27: 1623–1630.

    Article  Google Scholar 

  • Ball, R. C., Jullien, R. 1984. Finite size effects in cluster-cluster aggregation. J Physique Lett, 45: 1031–1035.

    Article  Google Scholar 

  • Bolla, M., Farrace, D., Wright, Y. M., Boulouchos, K. 2014. Modelling of soot formation in a heavy-duty diesel engine with conditional moment closure. Fuel, 117: 309–325.

    Article  Google Scholar 

  • Brasil, A. M., Farias, T. L., Carvalho, M. G. 1999. A recipe for image characterization of fractal-like aggregates. J Aerosol Sci, 30: 1379–1389.

    Article  Google Scholar 

  • Brenner, D. W. 1990. Empirical potential for hydrocarbons for use in simulating the chemical vapor deposition of diamond films. Phys Rev B, 42: 9458–9471.

    Article  Google Scholar 

  • Brookes, S. J., Moss, J. B. 1999. Predictions of soot and thermal radiation properties in confined turbulent jet diffusion flames. Combust Flame, 116: 486–503.

    Article  Google Scholar 

  • Burn, R. P., Mandelbrot, B. B. 1984. The Fractal Geometry of Nature. New York: W. H. Freeman and Company.

    Google Scholar 

  • Chan, M. L., Moody, K. N., Mullins, J. R, Williams, A. 1987. Low-temperature oxidation of soot. Fuel, 66: 1694–1698.

    Article  Google Scholar 

  • Chan, Q. N., Medwell, P. R., Nathan, G. J. 2014. Algorithm for soot sheet quantification in a piloted turbulent jet non-premixed natural gas flame. Exp Fluids, 55: 1827.

    Article  Google Scholar 

  • Chen, T. B. Y., Yuen, A. C. Y., Wang, C., Yeoh, G. H., Timchenko, V., Cheung, S. C. P., Chan, Q. N., Yang, W. 2018. Predicting the fire spread rate of a sloped pine needle board utilizing pyrolysis modelling with detailed gas-phase combustion. Int J Heat Mass Transf, 125: 310–322.

    Article  Google Scholar 

  • Cheung, S. C. P., Deju, L., Yeoh, G. H., Tu, J. Y. 2013. Modeling of bubble size distribution in isothermal gas-liquid flows: Numerical assessment of population balance approaches. Nucl Eng Des, 265: 120–136.

    Article  Google Scholar 

  • Cheung, S. C. P., Yeoh, G. H., Tu, J. Y. 2007. On the modelling of population balance in isothermal vertical bubbly flows—Average bubble number density approach. Chem Eng Process: Process Intensif, 46: 742–756.

    Article  Google Scholar 

  • Chishty, M. A., Bolla, M., Hawkes, E. R., Pei, Y., Kook, S. 2018. Soot formation modelling for n-dodecane sprays using the transported PDF model. Combust Flame, 192: 101–119.

    Article  Google Scholar 

  • Chittipotula, T., Janiga, G., Thévenin, D. 2011. Improved soot prediction models for turbulent non-premixed ethylene/air flames. Proc Combust Inst, 33: 559–567.

    Article  Google Scholar 

  • Choi, M., Altman, I. S., Kim, Y. J., Pikhitsa, P. V., Lee, S., Park, G. S., Jeong, T., Yoo, J. B. 2004. Formation of shell-shaped carbon nanoparticles above a critical laser power in irradiated acetylene. Adv Mater, 16: 1721–1725.

    Article  Google Scholar 

  • Coelho, P. J. 2007. Numerical simulation of the interaction between turbulence and radiation in reactive flows. Prog Energy Combust Sci, 33: 311–383.

    Article  Google Scholar 

  • Deju, L., Cheung, S. C. P., Yeoh, G. H., Tu, J. 2012. Study of isothermal vertical bubbly flow using direct quadrature method of moments. J Comput Multiph Flows, 4: 23–39.

    Article  MathSciNet  Google Scholar 

  • Deng, S., Mueller, M. E., Chan, Q. N., Qamar, N. H., Dally, B. B., Alwahabi, Z. T., Nathan, G. J. 2017. Hydrodynamic and chemical effects of hydrogen addition on soot evolution in turbulent nonpremixed bluff body ethylene flames. Proc Combust Inst, 36: 807–814.

    Article  Google Scholar 

  • Etheridge, J., Mosbach, S., Kraft, M., Wu, H., Collings, N. 2011. Modelling soot formation in a DISI engine. Proc Combust Inst, 33: 3159–3167.

    Article  Google Scholar 

  • Fairweather, M., Jones, W. P., Lindstedt, R. P. 1992. Predictions of radiative transfer from a turbulent reacting jet in a cross-wind. Combust Flame, 89: 45–63.

    Article  Google Scholar 

  • Fontanesi, S., del Pecchia, M., Pessina, V., Sparacino, S., di Iorio, S. 2021. Quantitative investigation on the impact of injection timing on soot formation in a GDI engine with a customized sectional method. Int J Engine Res, https://doi.org/10.1177/1468087421993955.

  • Fuchs, N. A. 1965. The mechanics of aerosols. By N. A. Fuchs. Translated by R. E. Daisley and Marina Fuchs; Edited by C. N. Davies. London (Pergamon Press), 1964. Pp. xiv, 408; 82 Figures; 40 Tables. £6. Q J R Meteorol Soc, 91: 249.

    Article  Google Scholar 

  • Goudeli, E., Eggersdorfer, M. L., Pratsinis, S. E. 2016. Coagulation of agglomerates consisting of polydisperse primary particles. Langmuir, 32: 9276–9285.

    Article  Google Scholar 

  • Guo, H., Liu, F., Smallwood, G. J., Gülder, Ö. L. 2002. The flame preheating effect on numerical modelling of soot formation in a two-dimensional laminar ethylene-air diffusion flame. Combust Theory Model, 6: 173–187.

    Article  Google Scholar 

  • Harris, S. J., Maricq, M. M. 2002. The role of fragmentation in defining the signature size distribution of diesel soot. J Aerosol Sci, 33: 935–942.

    Article  Google Scholar 

  • Haynes, B. S., Wagner, H. G. 1981. Soot formation. Prog Energy Combust Sci, 7: 229–273.

    Article  Google Scholar 

  • Heinson, W. R., Sorensen, C. M., Chakrabarti, A. 2010. Does shape anisotropy control the fractal dimension in diffusion-limited cluster-cluster aggregation? Aerosol Sci Technol, 44: i–iv.

    Article  Google Scholar 

  • Hou, D., Lindberg, C. S., Manuputty, M. Y., You, X., Kraft, M. 2019. Modelling soot formation in a benchmark ethylene stagnation flame with a new detailed population balance model. Combust Flame, 203: 56–71.

    Article  Google Scholar 

  • Inci, G., Kronenburg, A., Weeber, R., Pflüger, D. 2017. Langevin dynamics simulation of transport and aggregation of soot nano-particles in turbulent flows. Flow Turbul Combust, 98: 1065–1085.

    Article  Google Scholar 

  • Kelesidis, G. A., Goudeli, E., Pratsinis, S. E. 2017a. Morphology and mobility diameter of carbonaceous aerosols during agglomeration and surface growth. Carbon, 121: 527–535.

    Article  Google Scholar 

  • Kelesidis, G. A., Goudeli, E., Pratsinis, S. E. 2017b. Flame synthesis of functional nanostructured materials and devices: Surface growth and aggregation. Proc Combust Inst, 36: 29–50.

    Article  Google Scholar 

  • Kent, J. H., Wagner, H. G. 1984. Why do diffusion flames emit smoke. Combust Sci Technol, 41: 245–269.

    Article  Google Scholar 

  • Khan, I. M, Wang, C. H. T., Langridge, B. E. 1971. Coagulation and combustion of soot particles in diesel engines. Combust Flame, 17: 409–419.

    Article  Google Scholar 

  • Kholghy, M., Saffaripour, M., Yip, C., Thomson, M. J. 2013. The evolution of soot morphology in a laminar coflow diffusion flame of a surrogate for Jet A-1. Combust Flame, 160: 2119–2130.

    Article  Google Scholar 

  • Köylü, Ü. Ö., McEnally, C. S., Rosner, D. E., Pfefferle, L. D. 1997. Simultaneous measurements of soot volume fraction and particle size/microstructure in flames using a thermophoretic sampling technique. Combust Flame, 110: 494–507.

    Article  Google Scholar 

  • Kruis, F. E., Kusters, K. A., Pratsinis, S. E., Scarlett, B. 1993. A simple model for the evolution of the characteristics of aggregate particles undergoing coagulation and sintering. Aerosol Sci Technol, 19: 514–526.

    Article  Google Scholar 

  • Kubicki, J. D. 2000. Molecular mechanics and quantum mechanical modeling of hexane soot structure and interactions with pyrene. Geochem Trans, 1: 41.

    Article  Google Scholar 

  • Kwon, H., Etz, B. D., Montgomery, M. J., Messerly, R., Shabnam, S., Vyas, S., van Duin, A. C. T., McEnally, C. S., Pfefferle, L. D., Kim, S., Xuan, Y. 2020. Reactive molecular dynamics simulations and quantum chemistry calculations to investigate soot-relevant reaction pathways for hexylamine isomers. J Phys Chem A, 124: 4290–4304.

    Article  Google Scholar 

  • Kwon, H., Xuan, Y. 2021. Pyrolysis of bio-derived dioxolane fuels: A ReaxFF molecular dynamics study. Fuel, 306: 121616.

    Article  Google Scholar 

  • Lee, J., Yang, S. Y. 2013. A study of stability and vibration for particle sampling probes. Int J Mech Sci, 76: 152–157.

    Article  Google Scholar 

  • Leung, K. M., Lindstedt, R. P., Jones, W. P. 1991. A simplified reaction mechanism for soot formation in nonpremixed flames. Combusti Flame, 87: 289–305.

    Article  Google Scholar 

  • Li, D. D., Chan, Q. N., Timchenko, V., Yeoh, G. H. 2021. Controlling the clustering behavior of particulate colloidal systems using alternating and rotating magnetic fields. Comput Part Mech, https://doi.org/10.1007/s40571-021-00411-3.

  • Li, D. D., Gu, X., Timchenko, V., Chan, Q. N., Yuen, A. C. Y., Yeoh, G. H. 2018. Study of morphology and optical properties of gold nanoparticle aggregates under different pH conditions. Langmuir, 34: 10340–10352.

    Article  Google Scholar 

  • Li, D. D., Yeoh, G. H., Timchenko, V., Lam, H. F. 2016. Numerical modelling of magnetic nanoparticle and carrier fluid interactions. In: Proceedings of the IEEE Nanotechnology Materials and Devices Conference, Toulouse, France.

  • Li, D. D., Yeoh, G. H., Timchenko, V., Lam, H. F. 2017. Numerical modeling of magnetic nanoparticle and carrier fluid interactions under static and double-shear flows. IEEE Trans Nanotechnol, 16: 798–805.

    Article  Google Scholar 

  • Liu, F., Guo, H., Smallwood, G. J., Gülder, Ö. L. 2003. Numerical modelling of soot formation and oxidation in laminar coflow non-smoking and smoking ethylene diffusion flames. Combust Theory Model, 7: 301–315.

    Article  Google Scholar 

  • Liu, F., Mo, X., Gan, H., Guo, T., Wang, X., Chen, B., Chen, J., Deng, S., Xu, N., Sekiguchi, T., Golberg, D., Bando, Y. 2014. Cheap, gram-scale fabrication of BN nanosheets via substitution reaction of graphite powders and their use for mechanical reinforcement of polymers. Sci Rep, 4: 4211.

    Article  Google Scholar 

  • Mao, Q., van Duin, A. C. T., Luo, K. H. 2017. Formation of incipient soot particles from polycyclic aromatic hydrocarbons: A ReaxFF molecular dynamics study. Carbon, 121: 380–388.

    Article  Google Scholar 

  • Marchisio, D. L., Barresi, A. A. 2009. Investigation of soot formation in turbulent flames with a pseudo-bivariate population balance model. Chem Eng Sci, 64: 294–303.

    Article  Google Scholar 

  • Marchisio, D. L., Fox, R. O. 2005. Solution of population balance equations using the direct quadrature method of moments. J Aerosol Sci, 36: 43–73.

    Article  Google Scholar 

  • Marchisio, D. L., Pikturna, J. T., Fox, R. O., Vigil, R. D., Barresi, A. A. 2003. Quadrature method of moments for population-balance equations. AIChE J, 49: 1266–1276.

    Article  Google Scholar 

  • McEnally, C. S., Köylü, Ü. Ö., Pfefferle, L. D., Rosner, D. E. 1997. Soot volume fraction and temperature measurements in laminar nonpremixed flames using thermocouples. Combust Flame, 109: 701–720.

    Article  Google Scholar 

  • McEnally, C. S., Schaffer, A. M., Long, M. B., Pfefferle, L. D., Smooke, M. D., Colket, M. B., Hall, R. J. 1998. Computational and experimental study of soot formation in a coflow, laminar ethylene diffusion flame. Symp Combust, 27: 1497–1505.

    Article  Google Scholar 

  • McGraw, R. 1997. Description of aerosol dynamics by the quadrature method of moments. Aerosol Sci Technol, 27: 255–265.

    Article  Google Scholar 

  • Medwell, P. R., Nathan, G. J., Chan, Q. N., Alwahabi, Z. T., Dally, B. B. 2011. The influence on the soot distribution within a laminar flame of radiation at fluxes of relevance to concentrated solar radiation. Combust Flame, 158: 1814–1821.

    Article  Google Scholar 

  • Megaridis, C. M., Dobbins, R. A. 1989. Soot aerosol dynamics in a laminar ethylene diffusion flame. Symp Combust, 22: 353–362.

    Article  Google Scholar 

  • Mehta, R. S. 2008. Detailed modeling of soot formation and turbulence-radiation interactions in turbulent jet flames. Ph.D. Thesis. The Pennsylvania State University

  • Moss, J. B., Aksit, I. M. 2007. Modelling soot formation in a laminar diffusion flame burning a surrogate kerosene fuel. Proc Combust Inst, 31: 3139–3146.

    Article  Google Scholar 

  • Moss, J. B., Stewart, C. D. 1998. Flamelet-based smoke properties for the field modelling of fires. Fire Saf J, 30: 229–250.

    Article  Google Scholar 

  • Moss, J. B., Stewart, C. D., Syed, K. J. 1989. Flowfield modelling of soot formation at elevated pressure. Symp Combust, 22: 413–423.

    Article  Google Scholar 

  • Moss, J. B., Stewart, C. D., Young, K. J. 1995. Modeling soot formation and burnout in a high temperature laminar diffusion flame burning under oxygen-enriched conditions. Combust Flame, 101: 491–500.

    Article  Google Scholar 

  • Mueller, M. E., Chan, Q. N., Qamar, N. H., Dally, B. B., Pitsch, H., Alwahabi, Z. T., Nathan, G. J. 2013. Experimental and computational study of soot evolution in a turbulent nonpremixed bluff body ethylene flame. Combust Flame, 160: 1298–1309.

    Article  Google Scholar 

  • Ong, J. C., Pang, K. M., Walther, J. H., Ho, J. H., Ng, H. K. 2018. Evaluation of a Lagrangian Soot Tracking Method for the prediction of primary soot particle size under engine-like conditions. J Aerosol Sci, 115: 70–95.

    Article  Google Scholar 

  • Qamar, N. H., Nathan, G. J., Alwahabi, Z. T., Chan, Q. N. 2011. Soot sheet dimensions in turbulent nonpremixed flames. Combust Flame, 158: 2458–2464.

    Article  Google Scholar 

  • Rigopoulos, S. 2019. Modelling of soot aerosol dynamics in turbulent flow. Flow, Turbul Combust, 103: 565–604.

    Article  Google Scholar 

  • Saffaripour, M., Veshkini, A., Kholghy, M., Thomson, M. J. 2014. Experimental investigation and detailed modeling of soot aggregate formation and size distribution in laminar coflow diffusion flames of Jet A-1, a synthetic kerosene, and n-decane. Combust Flame, 161: 848–863.

    Article  Google Scholar 

  • Said, R., Garo, A., Borghi, R. 1997. Soot formation modeling for turbulent flames. Combust Flame, 108: 71–86.

    Article  Google Scholar 

  • Salenbauch, S., Sirignano, M., Marchisio, D. L., Pollack, M., D’Anna, A., Hasse, C. 2017. Detailed particle nucleation modeling in a sooting ethylene flame using a Conditional Quadrature Method of Moments (CQMOM). Proc Combust Inst, 36: 771–779.

    Article  Google Scholar 

  • Salenbauch, S., Sirignano, M., Pollack, M., D’Anna, A., Hasse, C. 2018. Detailed modeling of soot particle formation and comparison to optical diagnostics and size distribution measurements in premixed flames using a method of moments. Fuel, 222: 287–293.

    Article  Google Scholar 

  • Schuetz, C. A., Frenklach, M. 2002. Nucleation of soot: Molecular dynamics simulations of pyrene dimerization. Proc Combust Inst, 29: 2307–2314.

    Article  Google Scholar 

  • Shaddix, C., Williams, T. 2007. Soot: Giver and taker of light. Am Sci, 95: 232–239.

    Article  Google Scholar 

  • Singh, B. P., Kaviany, M. 1992. Modelling radiative heat transfer in packed beds. Int J Heat Mass Trans, 35: 1397–1405.

    Article  Google Scholar 

  • Sorensen, C. M. 2011. The mobility of fractal aggregates: A review. Aerosol Sci Technol, 45: 765–779.

    Article  Google Scholar 

  • Syed, K. J., Stewart, C. D., Moss, J. B. 1991. Modelling soot formation and thermal radiation in buoyant turbulent diffusion flames. Symp Combust, 23: 1533–1541.

    Article  Google Scholar 

  • Tersoff, J. 1988. Empirical interatomic potential for carbon, with applications to amorphous carbon. Phys Rev Lett, 61: 2879–2882.

    Article  Google Scholar 

  • Tree, D. R., Svensson, K. I. 2007. Soot processes in compression ignition engines. Prog Energy Combust Sci, 33: 272–309.

    Article  Google Scholar 

  • Turns, S. R. 2000. An Introduction to Combustion: Concepts and Applications, 2nd edn. Boston, MA, USA: McGraw-Hill.

    Google Scholar 

  • Van Duin, A. C. T., Dasgupta, S., Lorant, F., Goddard, W. A. 2001. ReaxFF: A reactive force field for hydrocarbons. J Phys Chem A, 105: 9396–9409.

    Article  Google Scholar 

  • Violi, A., Sarofim, A. F., Voth, G. A. 2004. Kinetic Monte Carlo-molecular dynamics approach to model soot inception. Combust Sci Technol, 176: 991–1005.

    Article  Google Scholar 

  • Virtanen, A. K. K., Ristimäki, J. M., Vaaraslahti, K. M., Keskinen, J. 2004. Effect of engine load on diesel soot particles. Environ Sci Technol, 38: 2551–2556.

    Article  Google Scholar 

  • Vishwanathan, G., Reitz, R. D. 2010. Development of a practical soot modeling approach and its application to low-temperature diesel combustion. Combust Sci Technol, 182: 1050–1082.

    Article  Google Scholar 

  • Wang, C., Chan, Q. N., Kook, S., Hawkes, E. R., Lee, J., Medwell, P. R. 2016. External irradiation effect on the growth and evolution of in-flame soot species. Carbon, 102: 161–171.

    Article  Google Scholar 

  • Wang, C., Yuen, A. C. Y., Chan, Q., Chen, T. B. Y., Yang, W., Cheung, S. C. P., Yeoh, G. H. 2019. Sensitivity analysis of key parameters for population balance based soot model for low-speed diffusion flames. Energies, 12: 910.

    Article  Google Scholar 

  • Wang, C., Yuen, A. C. Y., Chan, Q., Chen, T. B. Y., Yang, W., Cheung, S. C. P., Yeoh, G. H. 2020. Characterisation of soot particle size distribution through population balance approach and soot diagnostic techniques for a buoyant non-premixed flame. J Energy Inst, 93: 112–128.

    Article  Google Scholar 

  • Wang, H. 2011. Formation of nascent soot and other condensed-phase materials in flames. Proc Combust Inst, 33: 41–67.

    Article  Google Scholar 

  • Wang, Y., Raj, A., Chung, S. H. 2015. Soot modeling of counterflow diffusion flames of ethylene-based binary mixture fuels. Combust Flame, 162: 586–596.

    Article  Google Scholar 

  • Yang, J. C. 1993. Environmental Implications of Combustion Processes. Boca Raton, FA, USA: CRC Press.

    Google Scholar 

  • Yapp, E. K. Y., Chen, D., Akroyd, J., Mosbach, S., Kraft, M., Camacho, J., Wang, H. 2015. Numerical simulation and parametric sensitivity study of particle size distributions in a burner-stabilised stagnation flame. Combust Flame, 162: 2569–2581.

    Article  Google Scholar 

  • Ye, Y., Luo, X., Dong, C., Xu, Y., Zhang, Z. 2020. Numerical and experimental investigation of soot suppression by acoustic oscillated combustion. ACS Omega, 5: 23866–23875.

    Article  Google Scholar 

  • Yeoh, G. H., Tu, J. 2010. Computational Techniques for Multiphase Flows. UK: Butterworth-Heinemann.

    Google Scholar 

  • Yeoh, G. H., Yuen, K. K. 2009. Computational Fluid Dynamics in Fire Engineering. UK: Butterworth-Heinemann.

    Google Scholar 

  • Yeoh, G. H., Yuen, R. K. K., Chueng, S. C. P., Kwok, W. K. 2003. On modelling combustion, radiation and soot processes in compartment fires. Build Environ, 38: 771–785.

    Article  Google Scholar 

  • Yuan, C., Fox, R. O. 2011. Conditional quadrature method of moments for kinetic equations. J Comput Phys, 230: 8216–8246.

    Article  MathSciNet  MATH  Google Scholar 

  • Yuan, C., Laurent, F., Fox, R. O. 2012. An extended quadrature method of moments for population balance equations. J Aerosol Sci, 51: 1–23.

    Article  Google Scholar 

  • Yuen, A. C. Y., Yeoh, G. H., Alexander, B., Cook, M. 2014. Fire scene investigation of an arson fire incident using computational fluid dynamics based fire simulation. Build Simul, 7: 477–487.

    Article  Google Scholar 

  • Yuen, A. C. Y., Yeoh, G. H., Timchenko, V., Chen, T. B. Y., Chan, Q. N., Wang, C., Li, D. D. 2017. Comparison of detailed soot formation models for sooty and non-sooty flames in an under-ventilated ISO room. Int J Heat Mass Transf, 115: 717–729.

    Article  Google Scholar 

  • Yuen, A. C. Y., Yeoh, G. H., Timchenko, V., Cheung, S. C. P., Barber, T. J. 2016. Importance of detailed chemical kinetics on combustion and soot modelling of ventilated and under-ventilated fires in compartment. Int J Heat Mass Transf, 96: 171–188.

    Article  Google Scholar 

  • Yuen, A., Chen, T., Yang, W., Wang, C., Li, A., Yeoh, G., Chan, Q., Chan, M. 2019. Natural ventilated smoke control simulation case study using different settings of smoke vents and curtains in a large atrium. Fire, 2: 7.

    Article  Google Scholar 

  • Zhao, F., Yang, W., Yu, W. 2020a. A progress review of practical soot modelling development in diesel engine combustion. J Traffic Transp Eng (English Edition), 7: 269–281.

    Article  Google Scholar 

  • Zhao, F., Yang, W., Zhou, D., Yu, W., Li, J., Tay, K. L. 2017. Numerical modelling of soot formation and oxidation using phenomenological soot modelling approach in a dual-fueled compression ignition engine. Fuel, 188: 382–389.

    Article  Google Scholar 

  • Zhao, F., Yu, W., Su, W. 2016. Sensitivity study of engine soot forming using detailed soot modelling oriented in soot surface growth dynamic. Fuel, 168: 81–90.

    Article  Google Scholar 

  • Zhao, J., Lin, Y., Huang, K., Gu, M., Lu, K., Chen, P., Wang, Y., Zhu, B. 2020b. Study on soot evolution under different hydrogen addition conditions at high temperature by ReaxFF molecular dynamics. Fuel, 262: 116677.

    Article  Google Scholar 

  • Zucca, A., Marchisio, D. L., Barresi, A. A., Fox, R. O. 2006. Implementation of the population balance equation in CFD codes for modelling soot formation in turbulent flames. Chem Eng Sci, 61: 87–95.

    Article  Google Scholar 

  • Zucca, A., Marchisio, D. L., Vanni, M., Barresi, A. A. 2007. Validation of bivariate DQMOM for nanoparticle processes simulation. AIChE J, 53: 918–931.

    Article  Google Scholar 

Download references

Author information

Author notes

  1. Darson D. Li and Cheng Wang contributed equally to this work.

Authors and Affiliations

  1. School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Darson D. Li, Cheng Wang, Qing N. Chan & Guan H. Yeoh

  2. Australian Nuclear Science and Technology Organisation (ANSTO), Kirrawee DC, NSW, 2232, Australia

    Guan H. Yeoh

Authors
  1. Darson D. Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qing N. Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guan H. Yeoh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Darson D. Li or Cheng Wang.

Ethics declarations

The authors have no competing interests to declare that are relevant to the content of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, D.D., Wang, C., Chan, Q.N. et al. Soot: A review of computational models at different length scales. Exp. Comput. Multiph. Flow 5, 1–14 (2023). https://doi.org/10.1007/s42757-021-0124-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42757-021-0124-4

Keywords

Search

Navigation